Energy-Efficient joint Resource Allocation and Computation Offloading in NOMA-enabled Vehicular Fog Computing
Author:
Funder
2020 Science and Technology Innovation Team
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s11036-023-02265-w.pdf
Reference34 articles.
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5. Gao H, Qiu B, Barroso RJD, Hussain W, Xu Y, Wang X (2023) TSMAE: a novel anomaly detection approach for internet of things time series data using memory-augmented autoencoder. IEEE Trans Netw Sci Eng 10(5):2978–2990. https://doi.org/10.1109/TNSE.2022.3163144
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1. Energy‐efficient mechanisms for sustainable operations in vehicular fog networks: Challenges, state‐of‐the‐art, and future directions;International Journal of Communication Systems;2024-07-11
2. Design of load-aware resource allocation for heterogeneous fog computing systems;PeerJ Computer Science;2024-04-18
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